class_docstr: Class for Euclidean metrics.
  
  As a Riemannian metric, the Euclidean metric is:
  
  - flat: the inner-product is independent of the base point;
  - positive definite: it has signature (dimension, 0, 0),
    where dimension is the dimension of the Euclidean space.
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docstr: Compute the inner-product matrix, independent of the base point.
  
  Parameters
  ----------
  base_point : array-like, shape=[..., dim]
      Base point.
      Optional, default: None.
  
  Returns
  -------
  inner_prod_mat : array-like, shape=[..., dim, dim]
      Inner-product matrix.
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code: def metric_matrix(self, base_point=None):
      """Compute the inner-product matrix, independent of the base point.
  
      Parameters
      ----------
      base_point : array-like, shape=[..., dim]
          Base point.
          Optional, default: None.
  
      Returns
      -------
      inner_prod_mat : array-like, shape=[..., dim, dim]
          Inner-product matrix.
      """
      dim = self._space.dim
      mat = gs.eye(dim)
      return repeat_out(
          self._space.point_ndim, mat, base_point, out_shape=(dim, dim)
      )
  
file_path: geomstats/geomstats/geometry/euclidean.py
imports: import geomstats.backend
  from geomstats.geometry.base import VectorSpace
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 1 for calling the EuclideanMetric obj's underlying member method code with example usage: obj.metric_matrix(base_point) and returns: repeat_out